ObjectiveTo explore the establishment of performance assessment indicators for the classification and grading of public health staff in district-level Centers for Disease Control and Prevention (CDCs), and to provide a basis for such evaluations. MethodsThrough literature review and group interviews, performance evaluation indicators were developed based on competency evaluation. Experts were invited to evaluate the weight of performance evaluation indicators for public health staff from different categories, with the average value used to represent the weight of each indicator. ResultsTwenty-nine experts from universities in Shanghai, municipal CDCs, and district CDCs participated, yielding an expert authority coefficient of 0.86. The performance evaluation indicators for department managers were categorized into three levels, with 4 indicators at the primary level, 16 indicators at the secondary level, and 42 indicators at the tertiary level, while those for general staff included 4 primary indicators, 15 secondary indicators, and 36 tertiary indicators. Significant differences were observed in the weight coefficients of the primary indicators (internal operations, professional work, and learning and growth) between department managers and general staff. The top three secondary indicators for department managers were department management, monitoring and prevention, and level of expertise. For mid-level and senior staff, the top three secondary indicators were monitoring and prevention, level of expertise, and research work. The top three secondary indicators for junior staff were monitoring and prevention, professional expertise, and professional attitude. No significant statistical differences were found among tertiary indicators. ConclusionThe developed performance evaluation indicators are reliable. Staff at different levels and classifications should be evaluated using different performance evaluation standards to accurately reflect individual performance and contributions.

OBJECTIVE To optimize the forming process of Yindan huoxue tongyu granules， and evaluate the quality of the granules. METHODS Taking forming rate， angle of repose， moisture， moisture absorption rate and dissolution rate as indexes， single factor experiment combined with Plackett-Burman design was adopted to screen key process parameters； analytic hierarchy process combined with entropy weight method and Box-Behnken response surface method were used to optimize the molding process of Yindan huoxue tongyu granules， and the forming process was verified. The relative homogeneity index， bulk density， vibration density， Hausner ratio， angle of repose， moisture and hygroscopicity were used as secondary physical indexes to establish the physical fingerprints of 10 batches of Yindan huoxue tongyu granules to evaluate particle quality consistency. RESULTS The optimal molding process of Yindan huoxue tongyu granules was as follows： mannitol as the fixed excipient， the drug-assisted ratio was 1∶1（m/m） and the drying time was 1 h； 90% ethanol was used as wetting agent and the amount of it was 32%， the drying temperature was 70 ℃. The results of validation tests showed that the average comprehensive score was 97.45， which was close to the predicted value of 97.18. The similarities between the physical fingerprints of 10 batches of Yindan huoxue tongyu granules prepared by the optimal molding process and the reference physical fingerprint were all higher than 0.99. CONCLUSIONS The molding process is stable and feasible， and the quality of Yindan huoxue tongyu granules produced is stable and controllable.

OBJECTIVE To evaluate the quality of Yindan huoxue tongyu granules. METHODS Taking high performance liquid chromatography with ultraviolet and evaporative light scattering detection as method， the fingerprint of 15 batches of Yindan huoxue tongyu granules was established， and similarity evaluation was performed by Similarity Evaluation System of Chromatographic Fingerprint of TCM （2012 edition） to determine common peaks. The common peaks were identified by comparing with reference substance chromatograms and single decoction piece chromatograms. Network pharmacology was used to screen out core targets and pathways of identified components， construct a “component-target-pathway” network diagram， and predict the pharmacodynamic components of Yindan huoxue tongyu granules， and the content determination of these components was carried out by the same method. RESULTS HPLC fingerprints of 15 batches of Yindan huoxue tongyu granules were characterized with 40 common peaks， and 17 components including salvianolic acid B， astragaloside Ⅳ， notoginsenoside R1， and ginkgolide A were identified. Network pharmacology predicted that 17 components mainly acted on 97 core targets and 137 pathways to exert their pharmacological effect. Average contents of 13 bioactive components in 15 batches of samples were 0.126 8， 0.232 0， 0.073 8， 0.353 2， 3.620 2， 0.191 0， 0.333 3， 0.317 4， 0.785 0， 0.538 2， 0.460 0， 2.475 1 and 0.347 7 mg/g， including calycosin-7-O-β-D-glucoside， rosmarinic acid， formononetin， lithospermic acid， salvianolic acid B， ononin， ginsenoside Rb1， ginsenoside Rd， ginkgolide C， ginkgolide A， ginkgolide B， notoginsenoside R1， and astragaloside Ⅳ. CONCLUSIONS The established fingerprint of Yindan huoxue tongyu granules can reflect the overall characteristics of the preparation. The content determination method for its pharmacodynamic components， developed in combination with network pharmacology， is accurate， reliable， and exhibits good repeatability， making it suitable for evaluating the quality of Yindan huoxue tongyu granules.

Debates persist regarding the efficacy and safety of azvudine, particularly its real-world outcomes. This study involved patients aged ≥60 years who were admitted to 25 hospitals in mainland China with confirmed SARS-CoV-2 infection between December 1, 2022, and February 28, 2023. Efficacy outcomes were all-cause mortality during hospitalization, the proportion of patients discharged with recovery, time to nucleic acid-negative conversion (T _NANC), time to symptom improvement (T _SI), and time of hospital stay (T _HS). Safety was also assessed. Among the 5884 participants identified, 1999 received azvudine, and 1999 matched controls were included after exclusion and propensity score matching. Azvudine recipients exhibited lower all-cause mortality compared with controls in the overall population (13.3% vs. 17.1%, RR, 0.78; 95% CI, 0.67-0.90; P = 0.001) and in the severe subgroup (25.7% vs. 33.7%; RR, 0.76; 95% CI, 0.66-0.88; P < 0.001). A higher proportion of patients discharged with recovery, and a shorter T _NANC were associated with azvudine recipients, especially in the severe subgroup. The incidence of adverse events in azvudine recipients was comparable to that in the control group (2.3% vs. 1.7%, P = 0.170). In conclusion, azvudine showed efficacy and safety in older patients hospitalized with COVID-19 during the SARS-CoV-2 omicron wave in China.

Cemental tear is a rare and indetectable condition unless obvious clinical signs present with the involvement of surrounding periodontal and periapical tissues. Due to its clinical manifestations similar to common dental issues, such as vertical root fracture, primary endodontic diseases, and periodontal diseases, as well as the low awareness of cemental tear for clinicians, misdiagnosis often occurs. The critical principle for cemental tear treatment is to remove torn fragments, and overlooking fragments leads to futile therapy, which could deteriorate the conditions of the affected teeth. Therefore, accurate diagnosis and subsequent appropriate interventions are vital for managing cemental tear. Novel diagnostic tools, including cone-beam computed tomography (CBCT), microscopes, and enamel matrix derivatives, have improved early detection and management, enhancing tooth retention. The implementation of standardized diagnostic criteria and treatment protocols, combined with improved clinical awareness among dental professionals, serves to mitigate risks of diagnostic errors and suboptimal therapeutic interventions. This expert consensus reviewed the epidemiology, pathogenesis, potential predisposing factors, clinical manifestations, diagnosis, differential diagnosis, treatment, and prognosis of cemental tear, aiming to provide a clinical guideline and facilitate clinicians to have a better understanding of cemental tear.
Humans ; Dental Cementum/injuries* ; Consensus ; Diagnosis, Differential ; Cone-Beam Computed Tomography ; Tooth Fractures/therapy*

Ischemic heart disease (IHD) is associated with high morbidity and mortality rates. Reperfusion therapy is the best treatment option for this condition. However, reperfusion can aggravate myocardial damage through a phenomenon known as myocardial ischemia/reperfusion (I/R) injury, which has recently gained the attention of researchers. Several studies have shown that Chinese herbal medicines and their natural monomeric components exert therapeutic effects against I/R injury. This review outlines the current knowledge on the pathological mechanisms through which mitochondria participate in I/R injury, focusing on the issues related to energy metabolism, mitochondrial quality control disorders, oxidative stress, and calcium. The mechanisms by which mitochondria mediate cell death have also been discussed. To develop a resource for the prevention and management of clinical myocardial I/R damage, we compiled the most recent research on the effects of Chinese herbal remedies and their monomer components.

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Objective To explore the application effect of a BOPPPS-based blended teaching model in adult nursing course.Methods A total of 188 undergraduate nursing students from the school of Nursing,Kunming Medical university,in the class of 2021 were enrolled as research subjects and grouped by classes(97 students in the control group and 91 students in the experimental group).During the teaching process,the control group and the experimental group respectively adopted the traditional teaching model and the blended teaching model based on BOPPPS.The teaching effect was evaluated through the pre-assessment and post-assessment theoretical scores,learning engagement,independent learning ability and teacher quality of the two groups of students.Results The differences between the pre-assessment and post-assessment theoretical scores of the two groups were statistically significant,and the scores of the experimental group were 86.80(78.73,94.09),which were higher than those of the control group 79.45(69.39,87.97)(P<0.05).There were also statistically significant differences in the scores of learning engagement and independent learning ability between the two groups after teaching(P<0.05).Conclusion The blended teaching model based on BOPPPS used in the teaching of adult nursing for undergraduate nursing students can effectively improve the teaching effect,which is conducive to improving their learning engagement and stimulating students'learning autonomy.

The goal of achieving elimination of schistosomiasis across all endemic counties in China by 2030 was proposed in the Outline of the Healthy China 2030 Plan. On June 16, 2023, the Action Plan to Accelerate the Elimination of Schistosomiasis in China (2023—2030) was jointly issued by National Disease Control and Prevention Administration and other 10 ministries, which deployed the targets and key tasks of the national schistosomiasis elimination programme in China. This article describes the progress of the national schistosomiasis control programme, analyzes the opportunities to eliminate schistosomiasis, and proposes targeted recommendations to tackle the challenges of schistosomiasis elimination, so as to accelerate the process towards schistosomiasis elimination and facilitate the building of a healthy China.

Objective:To aid in the detection of thyroid cancer by using deep learning to differentiate the unique bioimpedance parameter patterns of different thyroid tissues.Methods:An electrical impedance system was designed to measure 331 ex-vivo thyroid specimens from 321 patients during surgery. The impedance data was then analyzed with one dimensional convolution neural (1D-CNN) combining with long short-term memory (LSTM) network models of deep learning. In the process of analysis, we assigned 80% of the data to training set (1072/1340) and the remaining 20% data to the test set (268/1340). The performance of final model was assessed using receiver operating characteristic (ROC) curves. In addition, sensitivity, specificity, positive predictive value, negative predictive value, Youden index were applied to compare impedance model with ultrasound results.Results:The ROC curve of the two-classification (malignant /non-malignant tissue) model showed a good performance (area-under-the-curve AUC=0.94), with an overall accuracy of 91.4%. To better fit clinical practice, we further performed a three-classification (malignant/ benign/ normal tissue) model, of which the areas under ROC curve were 0.91, 0.85, 0.92 for normal, benign, and malignant group, respectively. The results indicated that the area under micro-average ROC curve and the macro-average ROC curve were 0.91 and 0.90, respectively. Moreover, compared with ultrasound, the impedance model exhibited higher specificity.Conclusions:A deep learning model (CNN-LSTM) trained by thyroid electrical impedance spectroscopy (EIS) parameters shows an excellent performance in distinguishing among different in-vitro thyroid tissues, which is promising for applications. In future clinical utility, our study does not replace existing tests, but rather complements others, thus contributing to therapeutic decision-making and management of thyroid disease.